Anticipation requires adaptation

Commentary on Romi Nijhawan Word Counts: Abstract: 62 words Main Text: 803 words References: XXX words Total Text: XXXX words Anticipation Requires Adaptation Christian Balkenius Lund University Cognitive Science Kungshuset, Lundagård 222 22 Lund Sweden +46-46-222 32 51 (for correspondence) christian.balkenius@lucs.lu.se http://www.lucs.lu.se Peter Gärdenfors Lund University Cognitive Science Kungshuset, Lundagård 222 22 Lund Sweden +46-46-222 48 17 (for correspondence) peter.gardenfors@lucs.lu.se http://www.lucs.lu.se Abstract: To successfully interact with a dynamic world, our actions must be guided by a continuously changing anticipated future. Such anticipations must be tuned to the processing delays in the nervous system as well as to the slowness of the body, something that requires constant adaptation of the predictive mechanisms which in turn require that sensory information is processed at different time scales. The target article presents and interesting analysis of visual prediction and we fully agree with the author that predictions need to be made at different levels of the sensory-motor processing. However, the article severely underestimates the complexity of anticipation in the sensory-motor system. In particular, it ignores the important question of how an anticipatory system can tune its predictions to internal and external delays as a result of experience. Consider the example of catching a ball. It is not sufficent to "modify the perceived position of the ball so that it matches the position of the moving hand". Instead such a task involves at least the following components that can be divided into a visual pursuit and a catch component. The trajectory of the ball needs to be anticipated even to just look at it (Balkenius and Johansson, 2007). Since visual processing followed by movements of the eyes are not instant, it is necessary to predict where the ball is right now to be able to fixate it while it is moving. We call this the anticipated now since any sensory code that is synchronous with an external state must be based on anticipation. The predictions resulting in the anticipated now may or may not be correct, but there is no way for the organism to correct these predictions until at a later time when the true sensory input becomes available. At this time, it is possible to adapt the earlier predictions to the actual sensory input. Something that requires that the earlier anticipation as well as the sensory information used for it are still available. This implies that at every moment, the sensory input is used both to anticipate the future and to adapt earlier predictions, but because of processing delays, it can not be used to code for the current state of the external world. Similarly, eye movements can not be based on the anticipated now, but must be controlled by the anticipated future. Looking at a moving object thus requires that the organism simultaneously maintains sensory information at five different time scales: the current sensory input, the anticipated now and future, and previous predictions of the now and the future. By combining information at the different time scales in an appropriate way, it is possible to both change the currently anticipated now and to make future predictions more accurate. Assuming the gaze system is correctly tuned, the temporal unfolding of the ongoing interaction with the visual target contains the information needed to predict the location of the ball in the future, but the task for the hand is not to move to any arbitrary point along the predicted trajectory of the ball. Instead, the sensory-motor system must direct the hand to the location where the ball will be once the motor command to reach that location has been executed. This introduces an additional type of complexity since the time in the future when the hand will catch the ball depends on properties of the arm and hand as well as on the ball. Although this is strictly also true for eye movements, the physical lag of the system becomes more critical for arm movements. The properties of the flash-lag effect becomes perfectly sensible within this framework. Since unexpected events can not become part of the anticipated now until after a processing delay they will be perceived as lagging any predictable event. Moreover, since point events are perfect predictors of themselves, an adaptive system will learn to let them replace any prediction based on prior information. In the flash-terminated condition, the flash becomes part of the anticipated now at the same time as the detection of the disappearance of the target. These should thus be perceived as simultaneous and occurring at their actual location. Once this information is received, the best prediction is that the moving object disappeared where it was at the time of the flash. This does not mean that the movement of the object is not extrapolated. It only suggests that that extrapolation is replaced by better information when it is available. Although it is possible that biased competition plays a role in this process, it may be sufficient to assume that a system which adapt its predictions to actual information will learn to behave in this way. It is clear that the number of different times scales that are necessary in the brain is much larger than the few described here. Since substantial delays influence all processing in the brain, it appears necessary to compensate for these by predictive mechanisms at all levels. This suggests that predictive abilities should be necessary at the level of individual neurons or at least local circuits. The ongoing dynamical interaction between different parts of the brain is not too different from that with the external world. References Balkenius, C. and Johansson, B. (2007). Anticipatory Models in Gaze Control: A Developmental Model. Cognitive Processing, 8, 167-174. Acknowledgement(s) This work was funded in part by the EU project MindRaces, FP6-511931.